Internet commerce grew massively and continues to grow, in part because it is a medium for marketing and communication that is susceptible to experimentation, with a well-defined feedback loop established by the act of clicking on a piece of content to follow a link. The simplicity of such a relationship between the content and the response, along with means of defining who is acting, that enables the testing and optimization of content through means such as Google Analytics, and has enabled business models such as pay-per-click due to the naturally closed loop of internet behavior.
A variety of communications channels have emerged in the last few years. They include social media, mobile devices, IPTV, in-store digital signage and digital billboards, among others. These channels are characterized by a great deal of control over the content that is presented and the ability to change the content readily. Most of these cannot be directly linked to many important viewer behaviors such as purchasing decisions, because they lack a distinct interactive behavior (analogous to a “click” in internet advertising). There is strong interest in finding ways to identify a return signal for each of these means of content presentation, both in forms that can isolate individual channels and for integrated systems across those channels that can measure the effects of combined content received from those multiple channels, and for purposes ranging from improving the effects of advertising campaigns to enhancing public health messaging to improving traffic control technologies.
Current efforts to capture the impact of content on behavior are centered either on token creation or data mining. Token creation involves introducing some additional behavior to link the promotion to an individual's purchase through methods such as Microsoft TAG, couponing programs such as Groupon, loyalty rewards programs and check-ins such as social media platforms. These approaches tend to produce small and biased samples as a result of the need to opt-in or take additional steps to utilize the token, and typically suffer from increased cost and complexity due to a need to actively induce users to participate in the token system. They also struggle to be adopted because the additional required behavior enabling measurement necessarily alters the within-location experience. Data mining requires a significant volume of data, and is limited to correlation studies, not active cause-and-effect experimentation.